The latest AI news, launches, models, companies and research — collected from official sources, research feeds and reporting, grouped into stories and ranked by the BharatHunt Trend Score.
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3337 stories
Continual Classification Beyond the Kernel Regime: Harnessing the Sparsity Bias of L2 Regularization in Diagonal Linear Networks. Reported by arXiv. Bharat Hunt files it under AI Research — the section covering papers, benchmarks, evaluations, interpretability and safety results.
ALTO: African and Levantine Tech-Facilitated Gender-Based Violence Corpus. The story centres on Fine-tuning. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability. Open the original report for the full detail.
Suppressing Misaligned Behaviors in Language Models, Durably. It centres on Fine-tuning, and also names AI Safety and GPT. Reported by arXiv. Bharat Hunt files it under AI Research and AI Models — the section covering papers, benchmarks, evaluations, interpretability and safety results.
Adversarial Speculative Reasoning Improves Long Horizon Agents. It centres on Inference, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under Open Source AI and AI Agents — the section covering open-weight models, permissive licences and community releases.
GSBR: Geometric Support Behavior Regularization for Online RL. It centres on Benchmarks, and also names GitHub. Reported by arXiv. Bharat Hunt files it under Generative AI and AI Regulation — the section covering text, image, audio and video generation — products and their output.
Knowingly Wrong: Training LLMs Against Their Own Beliefs can Induce Misalignment. The story centres on Fine-tuning. Reported by arXiv. Bharat Hunt files it under AI Models and AI Research — the section covering a new or updated model, its capabilities, benchmarks or availability.
What Does the Model See? Representation Validity in Multimodal LLM-Based Video Analysis. It centres on Multimodal, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models and AI Research — the section covering a new or updated model, its capabilities, benchmarks or availability.
$τ$-Rec-Books: A Disclosure-Controlled Benchmark for Requirement Elicitation in Agentic Recommender Systems. It centres on Benchmarks, and also names GitHub. Reported by arXiv. Bharat Hunt files it under AI Agents and AI Research — the section covering autonomous and tool-using systems, agent frameworks, MCP and orchestration.
Unrolled gradients in disguise: bridging interpolation-based and Jacobian regularization for stable neural dynamics. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability. Open the original report for the full detail.
Bridging Neural Tangent Kernel Analysis and Reinforcement Learning for Deep Function Approximation. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability. Open the original report for the full detail.
CausalXRL: Explainable Reinforcement Learning through Causal Graph Reasoning. The story centres on Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Research — the section covering papers, benchmarks, evaluations, interpretability and safety results. Open the original report for the full detail.
GraphNIAH: A Benchmark for Long-Context Reasoning over Real-World Graphs. It centres on Benchmarks, and also names Reliance Jio and GPT. Reported by arXiv. Bharat Hunt files it under AI Models and AI Research, and tracks it as India coverage — the section covering a new or updated model, its capabilities, benchmarks or availability.
Bharat Hunt links to original reporting and does not republish it. Headlines and links belong to their publishers; summaries and the trend ranking are ours. All AI stories
Stories in the last 24 hours, against the 24 before it. A change is shown only where the earlier window had enough coverage to compare against.
Our own 0-100 ranking, not an industry metric and not anyone else’s “trending” number. It combines how recently a story was covered (32%), how many independent publications covered it (28%), how fast that coverage is arriving right now (20%), how reliable those sources are (12%) and how many people opened the story (8%).
A story we cannot date carries no score at all rather than a made-up one, so some cards show no badge. Summaries are written by Bharat Hunt from the headline and the coverage — the original article is always the source of truth, and every link goes to the publisher.